jcloud 0.0.25

Simplify deploying and managing Jina projects on Jina Cloud

Simplify deploying and managing Jina projects on Jina Cloud

☁️ To the cloud! - Smoothly deploy a local project as a cloud service. Radically easy, no brainfuck.

🎯 Cut to the chase - One CLI with five commands to manage the lifecycle of your Jina projects.

🎟️ Early free access - Sneak peek at our stealthy cloud hosting platform. Built on latest cloud-native tech stack, we now host your Jina project and offer computational and storage resources, for free!

Install

pip install jcloud
jc -h

In case jc is already occupied by another tool, please use jcloud instead. If your pip install doesn't register bash command for you, you can do python -m jcloud -h.

Get Started

Login

jc login

You can use Google/Github account to register and login. Without login, you can do nothing.

Deploy a Jina Project

In Jina's idiom, a project is a Flow, which represents an end-to-end task such as indexing, searching, recommending. In the sequel, we will use "project" and "Flow" interchangeably.

A Flow can have two types of file structure:

A single YAML file

A self-contained YAML file, consisting of all configs at the Flow-level and Executor-level.

All Executors' uses must follow jinahub+docker://MyExecutor (from Jina Hub) to avoid any local file dependency.

e.g.-

# flow.yml
jtype: Flow
executors:
  - name: sentencizer
    uses: jinahub+docker://Sentencizer

To deploy,

jc deploy flow.yml

Local project

Just like a regular Python project, you can have sub-folders of Executor implementations; and a flow.yml on the top-level to connect all Executors together.

You can create an example local project using jc new. The default structure looks like

.
├── .env
├── executor1
│   ├── config.yml
│   ├── executor.py
│   └── requirements.txt
└── flow.yml

where,

• executor1 directory has all Executor related code/config. You can read the best practices for file structures. Multiple such Executor directories can be created.
• flow.yml Your Flow yaml.
• .env All environment variables used during deployment.

To deploy,

jc deploy ./hello

---

Flow is successfully deployed when you see:

You will get a Flow ID, say 84b8b495df. This ID is required to manage, view logs and remove the Flow.

As this Flow is deployed with default gRPC gateway (feel free changing it to http or websocket), you can use jina.Client to access it:

from jina import Client, Document

c = Client(host='grpcs://84b8b495df.wolf.jina.ai')
print(c.post('/', Document(text='hello')))

Resource request

By default, jcloud allocates 100M of RAM to each Executor. There might be cases where your Executor requires more memory. For example, DALLE-mini (generating image from text prompt) would need more than 100M to load the model. Here's how you can request for more memory while deploying the Flow (max 16G allowed per Executor).

jtype: Flow
with:
  protocol: http
executors:
  - name: dalle_mini
    uses: jinahub+docker://DalleMini
    resources:
      memory: 8G

Environment variables

Local project

• You can include your environment variables in the .env file in the local project and JCloud will take care of managing them.
• You can optionally pass a custom.env.

  jc deploy ./hello --env-file ./hello/custom.env
  

Local yaml

jc deploy flow.yml --env-file flow.env

View logs

To watch the logs in realtime.

jc logs 84b8b495df

You can also stream logs for a particular executor by passing its name.

jc logs 84b8b495df --executor sentencizer

Remove a Flow

jc remove 84b8b495df

Get the status of a Flow

jc status 84b8b495df

List all Flows on the cloud

jc list

You can only see the Flows deployed by you.

You can also filter your Flows by passing a status.

jc list --status DELETED

Verbose logs

To make the output more verbose, you can add --loglevel DEBUG before each CLI subcommand, e.g.

jc --loglevel DEBUG deploy toy.yml

gives you more comprehensive output.

FAQ

• Why does it take a while on every operation of jcloud?

  Because the event listener at Jina Cloud is serverless by design, which means it spawns an instance on-demand to process your requests from jcloud. Note that operation such as deploy, remove in jcloud is not high-frequent. Hence, having a serverless listener is much more cost-efficient than an always-on listener. The downside is slower operations, nevertheless this does not affect the deployed service. Your deployed service is always on.

• How long do you persist my service?

  Until you manually remove it, we will persist your service as long as possible.

• Is everything free?

  Yes! We just need your feedback - use jc survey to help us understand your needs.

• How powerful is Jina Cloud?

  Jina Cloud scales according to your need. You can demand for the resources your Flow requires. If there's anything particular you'd be looking for, you can contact us on Slack or let us know via jc survey.

• How do I send request to a HTTP server?

  First, you need to set the Flow protocol to http. Then make sure you are sending to /post endpoint, e.g.

  curl -X POST https://6893976a58.wolf.jina.ai/post -H 'Content-Type: application/json' -d '{"data":[{"text": "hello, world!"}], "execEndpoint":"/"}'
  

Support

• Check out the Learning Bootcamp to get started with DocArray.
• Join our Slack community and chat with other community members about ideas.
• Join our Engineering All Hands meet-up to discuss your use case and learn Jina's new features.
  • When? The second Tuesday of every month
  • Where? Zoom (see our public events calendar/.ical) and live stream on YouTube
• Subscribe to the latest video tutorials on our YouTube channel

Join Us

JCloud is backed by Jina AI and licensed under Apache-2.0. We are actively hiring AI engineers, solution engineers to build the next neural search ecosystem in open-source.